Abstract. To improve our knowledge of urban meteorology, including those processes applicable to high-resolution meteorological models in the Seoul Metropolitan Area, a Weather Information Service Engine urban meteorological observation system network (UMS-Seoul) has been designed and installed. The network incorporates 14 surface energy balance (EB) systems, 7 surface-based 3-dimensional meteorological observation (3D) systems, and applied meteorological observation (AP) systems, as well as the existing surface-based meteorological observation network. The EB system consists of a radiation balance system, sonic anemometers, infrared CO2/H2O gas analyzers, and many sensors to measure wind speed and direction, temperature and humidity, precipitation, and air pressure, etc. The EB-produced radiation, meteorological, and turbulence data will be used to quantify the surface energy balance according to land use, and improve the boundary layer and surface processes in meteorological models. The 3D system, composed of wind lidar, a microwave radiometer, an aerosol lidar, or a ceilometer, produces vertical profiles of backscatter by aerosols or water vapor, cloud height, wind speed and direction, temperature, humidity, and liquid water content. It will be used for high-resolution reanalysis data based on observations as well as for improvement of the boundary layer, radiation, and microphysics processes in meteorological models. The AP system includes road weather information, mosquito activity, and water quality observation instruments. The standardized metadata for networks and stations are documented and renewed periodically to provide a detailed observation environment. The UMS-Seoul data are designed to support real-time acquisition, as well as display and automatically quality check the data within 10 minutes of observation. After the quality check, data can be distributed to relevant potential users such as researchers and policy makers.

Future changes of land use and land cover (LULC) due to urbanization can cause variations in the frequency and severity of extreme weather events, affecting local climate and potentially worsening impact of such events. This work examines the local climatic impacts associated with projected urban expansion through simulations of rainfall and temperature over the rapidly growing city of the middle-eastern region in Tanzania. Simulations were conducted using a mesoscale Weather Research and Forecasting (WRF) model for a period of 10 days during the rainfall season in April 2018. The Global Forecasting System data of 0.25° resolution was used to simulate the WRF model in two-way nested domains at resolutions of 12 km and 4 km correspondingly. Urban and built-up areas under the current state, low urbanization (30%), and high urbanization (99%) scenarios were taken into account as LULC categories. As the urbanized area increased, daily mean, maximum and minimum air temperatures, as well as precipitation increased. Local circulation affected the spatial irregularities of air temperature and precipitation. Results imply that urbanization can amplify the impacts of future climate changes dramatically. These results can be applicable to the city planning to minimize the adverse effect of urbanization on temperature and precipitation.

No abstract

Vertical mixing in the planetary boundary layer (PBL) is an important factor in the prediction of particulate matter (PM) concentrations; however, PBL height (PBLH) in the stable atmosphere remains poorly understood. In particular, the assessment of uncertainties related to nocturnal PBLH (nPBLH) is challenging due to the absence of stable atmosphere observations. In this study, we explored nPBLH–PM2.5 interactions by comparing model results and observations during the Korea–United States Air Quality Study (KORUS-AQ) campaign (1–31 May 2016). Remote sensing measurements (e.g., aerosol and wind Doppler lidar) and on-line WRF-Chem modeling results were used by applying three different PBL parameterizations: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), and Asymmetrical Convective Model v2 (ACM2). Our results indicated that the uncertainties of PBLH–PM interactions were not large in daytime, whereas the uncertainties of nPBLH–PM2.5 interactions were significant. All WRF-Chem experiments showed a clear tendency to underestimate nighttime nPBLH by a factor of ~3 compared with observations, and shallow nPBLH clearly led to extremely high PM2.5 peaks during the night. These uncertainties associated with nPBLH and nPBLH–PM2.5 simulations suggest that PM2.5 peaks predicted from nighttime or next-morning nPBLH simulations should be interpreted with caution. Additionally, we discuss uncertainties among PBL parameterization schemes in relation to PM2.5 simulations.

No abstract